Instructions to use imxly/sentence_rtb3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imxly/sentence_rtb3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="imxly/sentence_rtb3")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("imxly/sentence_rtb3") model = AutoModel.from_pretrained("imxly/sentence_rtb3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ca64e2c513bcbebafc0197630ea3693424bdbfd3ece0a0b28434fcd698f49f0
- Size of remote file:
- 154 MB
- SHA256:
- 1b8de4241bf32ebfcfcc228b426f7fc3723eb692a4f1e8cb3548947530cac945
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.